14 machine-learning-and-image-processing Postdoctoral positions at Umeå University in Sweden
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-of-computing-science/ Project description and working tasks The project will develop privacy-aware machine learning (ML) models. We are interested in data driven models for complex data, including temporal data
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for physical AI and physics‑based simulation for complex mechanical systems. We are now seeking a postdoctoral researcher for a project aiming at physics‑informed autonomous control of machines operating in
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surgery. Description of the project and work responsibilities The project involves basic science and clinical research samples, with particular focus on the role of autologous fat in regenerative plastic
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ecosystem processes across elevational gradients in mountains (https://www.nature.com/articles/nature21027). Following from that work, and to better understand the mechanisms involved, about a decade ago we
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interpretation of culture and memory, as well as its influence on creativity and the dynamics of human-machine interaction. Second, it investigates how collaborations driven by AI are reshaping creative
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in radiotherapy with the goal of enabling fully adaptive radiotherapy. The work is based on deep learning, where models are trained on generated or clinical data. The project is carried out in
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loop/TAD structures. - Perform comparative analyses versus Populus tremula; apply network modelling and machine learning for regulatory inference. - Functional validation of candidate TE‑CREs in spruce
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well as state-of-the-art mucus measurements and imaging techniques. The specific work responsibilities of the postdoctoral researcher include: · Test how specific dietary supplements affect mucus
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will also use focussed ion beam milling scanning electron microscopy (FIB-SEM) to prepare infected cells for in situ cryo-ET. The resulting tomographic data will be analysed by machine-learning assisted
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, the establishment and optimization of behavioral assays under controlled oxygen conditions, image‑based analyses, and quantitative data processing and interpretation. The role also includes active participation in